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GECCO
2009
Springer

Sustaining diversity using behavioral information distance

8 years 10 months ago
Sustaining diversity using behavioral information distance
Conventional similarity metrics used to sustain diversity in evolving populations are not well suited to sequential decision tasks. Genotypes and phenotypic structure are poor predictors of how solutions will actually behave in the environment. In this paper, we propose measuring similarity directly on the behavioral trajectories of evolving candidate policies using a universal similarity measure based on algorithmic information theory: normalized compression distance (NCD). NCD is compared to four other similarity measures in both genotype and phenotype space on the POMDP Tartarus problem, and shown to produce the most fit, general, and complex solutions. Categories and Subject Descriptors I.2.8 [Artificial Intelligence]: Problem Solving, Control Methods, and Search—heuristic methods General Terms Algorithms
Faustino J. Gomez
Added 26 May 2010
Updated 26 May 2010
Type Conference
Year 2009
Where GECCO
Authors Faustino J. Gomez
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